Position/Title: PhD Student
- University of Guelph - Doctor of Philosophy in Animal Biosciences (Present)
- University of Alberta - Masters of Science in Agriculture, Food, and Nutritional Sciences, Animal Science (2020)
- University of Alberta - Bachelor of Science with Honours in Molecular Genetics (2016)
My experience with the livestock industry began at the University of Alberta where I completed a MSc in Animal Science, and ever since, I have taken every opportunity to immerse myself in the industry. During this program, I conducted research focused on genomic selection in pigs, aiming to uncover the genetic and biological factors that influence meat and carcass quality traits.
In addition to my thesis, I undertook an 18-month internship through the MITACS accelerate fellowship with Hypor Inc., a swine breeding and genetics company. This internship provided me with a comprehensive understanding of various aspects of pig production, including the operations on farms, abattoirs, and industry offices. I also had the opportunity to work collaboratively with Hypor Inc. and Animal Inframetrics, a company that develops and implements infrared thermography (IRT) technologies for animal phenotyping. This project focused on evaluating IRT traits as suitable indicators for the genetic improvement of feed efficiency in pigs, employing innovative technologies, 'big data' analytics, and genetic analysis. These experiences solidified my passion for leveraging breeding and genetics to address the present-day challenges faced by the livestock industry.
For my PhD I am involved in a three-year project under the guidance of Dr. Angela Cánovas and Dr. Flavio Schenkel. The project is a collaboration between the University of Guelph and AgSights, an industry partner.
The advancement of high-throughput technologies presents a significant opportunity for beef cattle producers to enhance the genetics of their herds and maintain competitiveness in the future meat market. However, as datasets continue to grow in size and complexity, and novel data sources emerge, it becomes essential to have an efficient and flexible genetic evaluation system (GES) in place. These systems play a crucial role in translating data into meaningful insights for producers to make informed breeding decisions. AgSights provides a user-friendly GES, but given the future expectations for data acquisition and the increasing demand for more comprehensive evaluations, updates and enhancements are necessary to ensure that the system remains at the forefront of genetic evaluation technology. Therefore, this project aims, 1) to enhance the flexibility of AgSights' GES to efficiently evaluate novel and high-throughput phenotypes, 2) to assess the feasibility of integrating genomic information into a single-step genomic evaluation procedure for muti-breed and crossbred beef cattle. The outcomes of this study will be incorporated into AgSights Go360|bioTrack tool, enabling the selection of novel and high-throughput phenotypes in beef cattle.
Through my PhD project, in collaboration with AgSights, I am excited to contribute to the advancement of the genetic evaluation system and help shape the future of beef cattle genetics. By using cutting-edge technologies, implementing innovative methodologies, and addressing the challenges associated with the rapid influx of data data, we aim to create a GES that is aligned with the industry's needs and facilitates the utilization of genetic information to drive progress and profitability in the beef cattle sector.